1. Field of the Invention
This invention relates to a method and an apparatus for management of an operation of a blast furnace in the iron industry.
2. Description of the Related Art
A blast furnace in the iron industry has to be operated taking into account numerous operational factors relating to each other. Furthermore, as it is difficult to directly view the inside of the furnace due to restrictions of the equipment, etc., numerous sensors of various types are attached to the equipment. Therefore, a comprehensive estimation based on information from the sensors, etc., and an optimum control according to the estimation, are required to maintain and improve the level of operation. In this regard, the experience and knowledge of operators are valuable and important for the routine management of the operation of the blast furnace, even at the present time.
As in an expert system, the aforementioned human know-how can be programmed into a computer and be executed, and the introduction of an expert system into the management of the operation of a blast furnace is disclosed in Japanese Unexamined Patent Publication (Kokai) Nos. 64-270708 and 62-270712. By systematization of the management of the operation of a blast furnace, the problems of an oversight of information or misjudgement are avoided, and rationalization and standardization of the management of the operation of the blase furnace are effectively carried out.
In the conventional method of the management of the operation of a blase furnace utilizing an expert system as disclosed in the aforementioned publications, as the results obtained by the inference are a forecast of channeling and slip, and a decision regarding heat level in the furnace, the inference is independently carried out for each respective matter among the phenomena occurring inside the furnace, by providing knowledge bases with regard to these matters.
However, the phenomena inside the furnace such as permeation of gas, burden descent, and heat level of the furnace, etc., are correlated with each other as an integrated process inside the blast furnace, and therefore, it is necessary to comprehensively recognize the individual phenomena to decide actions to take in a blast furnace operation management system. To realize the above management, a large capacity knowledge base which derives final actions from a great deal of information regarding the blast furnace, is required.
Furthermore, as another important matter required in the blast furnace operation management system, recognization of the transition of a condition inside the blast furnace, which is a continuous reaction furnace, and a decision of the actions in response to the transition have to be immediately carried out. In other words, an interval of inference must be as short as possible. Nevertheless, the interval of inference is inevitably limited by the execution time for preparation of data for the inference, execution of the inference, etc. The interval of inference using a knowledge base having a large capacity to handle a great deal of information cannot be shortened because of the long execution time required to access the knowledge base. Therefore, there is a problem that if a large capacity knowledge base is used to comprehensively recognize and judge the condition inside the blast furnace, then the speed of the decision making process is reduced. On the other hand, if a small capacity knowledge base is used to shorten the interval of the inference, then the decision making process becomes inadequate.
Meanwhile, among actions taken in routine operation, there are a retreat action (defensive action) such as elevation of a fuel rate and reduction of blasting quantity to avoid malfunction of the furnace, a restorative action (offensive action) such as reduction of the fuel rate to reduce operational cost when the operation condition becomes stable after the retreat action and an operation level improvement action.
Therefore, the inference for management of an operation of the blast furnace has to include various types of inference processes for the above various kinds of operations to cover all the routine operations, and the inference has to be constructed considering the above dispositions of the operations.
Burden distribution, i.e., distribution of ore and coke piled within the blast furnace, is an important factor in maintaining a stable state of the furnace over a long period of time. Therefore, fine control of the distribution depending on the state of the furnace is necessary to keep the operation stable. Past experience and knowledge are effective in diagnosis of requirement of action regarding this distribution. However, sometimes even experience and knowledge are not effective in deciding optimum actions according to a diagnosis. An action decided by deducting only from past experience and knowledge sometimes yields an unexpected result. The reason is that there are many factors, for example, the shooting position of the burden, the way of sharing the burden, the quantity of each shared burden, the stock level, etc., which affect the distribution, and also that a different result occurs even though control conditions are the same if the condition of the raw material, such as the grading distribution of the raw material, is different. Therefore, it is difficult to deduce an optimum action for controlling the burden distribution only by inference with a knowledge base based on past experience and knowledge.
Additionally, operational conditions in the blast furnace change remarkably during the life time of the furnace due to age deterioration of the profile of the blast furnace due to wearing of the furnace bricks, and variation in the condition of raw materials. For this reason, the operation management system for the blast furnace must be able to be easily maintained so as to be utilized during the life time of the furnace.
As the knowledge base is a kind of program, repeated test inference is necessary for estimation of whether the inference is adequate when the knowledge base is modified to cope with the change of the operational circumstance. Furthermore, debugging work is required when bugs are found in the knowledge base. In the aforementioned conventional system, a problem arises in that the inference for management of operation must be interrupted during the test run or the debugging work.